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Ranjan Ganguli

Researcher at Indian Institute of Science

Publications -  326
Citations -  6442

Ranjan Ganguli is an academic researcher from Indian Institute of Science. The author has contributed to research in topics: Finite element method & Helicopter rotor. The author has an hindex of 43, co-authored 324 publications receiving 5900 citations. Previous affiliations of Ranjan Ganguli include University of Maryland, College Park & Indian Institute of Technology Kharagpur.

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The Use of Kalman Filter and Neural Network Methodologies in Gas Turbine Performance Diagnostics: A Comparative Study

TL;DR: In this article, the authors compare the performance of the two most widely used methods for fault isolation, namely, Kalman filters and Artificial Neural Networks (ANNs), for a wide variety of commercial and military engines.
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Damage assessment of structures with uncertainty by using mode-shape curvatures and fuzzy logic

TL;DR: In this paper, a fuzzy logic-based approach for damage detection is proposed, where the authors show that geometric and measurement uncertainty cause considerable problem in damage assessment, which can be alleviated by using a probabilistic approach.
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Strength design of composite beam using gradient and particle swarm optimization

TL;DR: In this paper, a computationally efficient analytical model for box-beam is used to find the optimal design of a composite boxbeam structure subject to strength constraints, which can be used as the main load carrying members of helicopter rotor blades.
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Genetic fuzzy system for damage detection in beams and helicopter rotor blades

TL;DR: In this article, a genetic fuzzy logic system is proposed as a method for automatic rule generation in fuzzy systems for structural damage detection in a cantilever beam, and the output faults of the fuzzy system are four levels of damage (undamaged, slight, moderate, and severe).
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Survey of Recent Developments in Rotorcraft Design Optimization

TL;DR: The multidisciplinary nature of the helicopter engineering problems has led researchers to investigate formal optimization methods for the design process, but several issues have prevented it from becoming as popular or successful as structural optimization.